Deep Learning based Human Action Recognition

• Main Authors: Pandey Ritik, Chikhale Yadnesh, Verma Ritik, Patil Deepali
• Format: Article
• Language: English
• Published: EDP Sciences 2021-01-01
• Series: ITM Web of Conferences
• Online Access: https://www.itm-conferences.org/articles/itmconf/pdf/2021/05/itmconf_icacc2021_03014.pdf

Human action recognition has become an important research area in the fields of computer vision, image processing, and human-machine or human-object interaction due to its large number of real time applications. Action recognition is the identification of different actions from video clips (an arrangement of 2D frames) where the action may be performed in the video. This is a general construction of image classification tasks to multiple frames and then collecting the predictions from each frame. Different approaches are proposed in literature to improve the accuracy in recognition. In this paper we proposed a deep learning based model for Recognition and the main focus is on the CNN model for image classification. The action videos are converted into frames and pre-processed before sending to our model for recognizing different actions accurately..